Introduction: ai_position Department 2022

Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:

The method for the research-field-mapping can be reiviewed here:

Rakas, M., & Hain, D. S. (2019). The state of innovation system research: What happens beneath the surface?. Research Policy, 48(9), 103787.

Topic modelling

Topics by topwords

Topics over time

Knowledge Bases: Co-Citation network analysis

Note: This analysis refers the co-citation analysis, where the cited references and not the original publications are the unit of analysis. See tab Technical descriptionfor additional explanations

Knowledge Bases summary

Main Indicators

In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.

com name dgr_int dgr
Knowledge Base 1: KB 1
1 AUTOR D.H. LEVY F. MURNANE R.J. THE SKILL CONTENT OF RECENT TECHNOLOGICAL CHANGE: AN EMPIRICAL EXPLORATION (2003) 2422 2724
1 GOOS M. MANNING A. SALOMONS A. EXPLAINING JOB POLARIZATION: ROUTINE-BIASED TECHNOLOGICAL CHANGE AND OFFSHORING (2014) 1760 1920
1 ACEMOGLU D. AUTOR D. SKILLS TASKS AND TECHNOLOGIES: IMPLICATIONS FOR EMPLOYMENT AND EARNINGS (2011) 1645 1866
1 GOOS M. MANNING A. LOUSY AND LOVELY JOBS: THE RISING POLARIZATION OF WORK IN BRITAIN (2007) 1580 1730
1 AUTOR D.H. DORN D. THE GROWTH OF LOW-SKILL SERVICE JOBS AND THE POLARIZATION OF THE US LABOR MARKET (2013) 1332 1561
1 GOOS M. MANNING A. SALOMONS A. JOB POLARIZATION IN EUROPE (2009) 878 939
1 SPITZ-OENER A. TECHNICAL CHANGE JOB TASKS AND RISING EDUCATIONAL DEMANDS: LOOKING OUTSIDE THE WAGE STRUCTURE (2006) 876 927
1 FREY C.B. OSBORNE M.A. THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION? (2017) 665 923
1 KARABARBOUNIS L. NEIMAN B. THE GLOBAL DECLINE OF THE LABOR SHARE (2014) 525 550
1 AUTOR D.H. WHY ARE THERE STILL SO MANY JOBS? THE HISTORY AND FUTURE OF WORKPLACE AUTOMATION (2015) 519 711
Knowledge Base 2: KB 2
2 AUTOR D.H. DORN D. HANSON G.H. THE CHINA SYNDROME: LOCAL LABOR MARKET EFFECTS OF IMPORT COMPETITION IN THE UNITED STATES (2013) 1044 1546
2 EATON J. KORTUM S. TECHNOLOGY GEOGRAPHY AND TRADE (2002) 836 942
2 MELITZ M.J. THE IMPACT OF TRADE ON INTRA-INDUSTRY REALLOCATIONS AND AGGREGATE INDUSTRY PRODUCTIVITY (2003) 631 725
2 HEAD K. MAYER T. GRAVITY EQUATIONS: WORKHORSE TOOLKIT AND COOKBOOK (2014) 591 591
2 ANDERSON J.E. VAN WINCOOP E. GRAVITY WITH GRAVITAS: A SOLUTION TO THE BORDER PUZZLE (2003) 479 479
2 CALIENDO L. PARRO F. ESTIMATES OF THE TRADE AND WELFARE EFFECTS OF NAFTA (2015) 412 441
2 SIMONOVSKA I. WAUGH M.E. THE ELASTICITY OF TRADE: ESTIMATES AND EVIDENCE (2014) 389 412
2 ANDERSON J.E. A THEORETICAL FOUNDATION FOR THE GRAVITY EQUATION (1979) 311 311
2 ARKOLAKIS C. COSTINOT A. RODRÍGUEZ-CLARE A. NEW TRADE MODELS SAME OLD GAINS? (2012) 285 288
2 CHANEY T. DISTORTED GRAVITY: THE INTENSIVE AND EXTENSIVE MARGINS OF INTERNATIONAL TRADE (2008) 276 276
Knowledge Base 3: KB 3
3 TUSHMAN M.L. ANDERSON P. TECHNOLOGICAL DISCONTINUITIES AND ORGANIZATIONAL ENVIRONMENTS (1986) 1314 1334
3 CHRISTENSEN C.M. (1997) 647 660
3 HENDERSON R.M. CLARK K.B. ARCHITECTURAL INNOVATION: THE RECONFIGURATION OF EXISTING PRODUCT TECHNOLOGIES AND THE FAILURE OF ESTABLISHED FIRMS (1990) 490 506
3 MARCH J.G. EXPLORATION AND EXPLOITATION IN ORGANIZATIONAL LEARNING (1991) 330 342
3 COHEN W.M. LEVINTHAL D.A. ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION (1990) 318 328
3 TRIPSAS M. GAVETTI G. CAPABILITIES COGNITION AND INERTIA: EVIDENCE FROM DIGITAL IMAGING (2000) 291 294
3 LEONARD-BARTON D. CORE CAPABILITIES AND CORE RIGIDITIES: A PARADOX IN MANAGING NEW PRODUCT DEVELOPMENT (1992) 281 285
3 CHRISTENSEN C.M. BOWER J.L. CUSTOMER POWER STRATEGIC INVESTMENT AND THE FAILURE OF LEADING FIRMS (1996) 264 268
3 TEECE D.J. PISANO G. SHUEN A. DYNAMIC CAPABILITIES AND STRATEGIC MANAGEMENT (1997) 254 279
3 TRIPSAS M. UNRAVELING THE PROCESS OF CREATIVE DESTRUCTION: COMPLEMENTARY ASSETS AND INCUMBENT SURVIVAL IN THE TYPESETTER INDUSTRY (1997) 247 247
Knowledge Base 4: KB 4
4 PAOLACCI G. CHANDLER J. IPEIROTIS P.G. RUNNING EXPERIMENTS ON AMAZON MECHANICAL TURK (2010) 972 1002
4 GOODMAN J.K. CRYDER C.E. CHEEMA A. DATA COLLECTION IN A FLAT WORLD: THE STRENGTHS AND WEAKNESSES OF MECHANICAL TURK SAMPLES (2013) 645 667
4 HORTON J.J. RAND D.G. ZECKHAUSER R.J. THE ONLINE LABORATORY: CONDUCTING EXPERIMENTS IN A REAL LABOR MARKET (2011) 586 652
4 MASON W. SURI S. CONDUCTING BEHAVIORAL RESEARCH ON AMAZON’S MECHANICAL TURK (2012) 432 432
4 PAOLACCI G. CHANDLER J. INSIDE THE TURK: UNDERSTANDING MECHANICAL TURK AS A PARTICIPANT POOL (2014) 391 397
4 BUHRMESTER M. KWANG T. GOSLING S.D. AMAZON’S MECHANICAL TURK: A NEW SOURCE OF INEXPENSIVE YET HIGH-QUALITY DATA? (2011) 319 319
4 PEER E. VOSGERAU J. ACQUISTI A. REPUTATION AS A SUFFICIENT CONDITION FOR DATA QUALITY ON AMAZON MECHANICAL TURK (2014) 296 296
4 MASON W. SURI S. CONDUCTING BEHAVIORAL RESEARCH ON AMAZON’S MECHANICAL TURK (2012) 247 247
4 BUHRMESTER M. KWANG T. GOSLING S.D. AMAZON’S MECHANICAL TURK: A NEW SOURCE OF INEXPENSIVE YET HIGH-QUALITY DATA? (2011) 245 248
4 BERINSKY A.J. HUBER G.A. LENZ G.S. EVALUATING ONLINE LABOR MARKETS FOR EXPERIMENTAL RESEARCH: AMAZON.COM’S MECHANICAL TURK (2012) 217 217
Knowledge Base 5: KB 5
5 DIETVORST B.J. SIMMONS J.P. MASSEY C. ALGORITHM AVERSION: PEOPLE ERRONEOUSLY AVOID ALGORITHMS AFTER SEEING THEM ERR (2015) 241 245
5 DIETVORST B.J. SIMMONS J.P. MASSEY C. OVERCOMING ALGORITHM AVERSION: PEOPLE WILL USE IMPERFECT ALGORITHMS IF THEY CAN (EVEN SLIGHTLY) 213 216
5 HUANG M.H. RUST R.T. ARTIFICIAL INTELLIGENCE IN SERVICE (2018) 184 191
5 JARRAHI M.H. ARTIFICIAL INTELLIGENCE AND THE FUTURE OF WORK: HUMAN-AI SYMBIOSIS IN ORGANIZATIONAL DECISION MAKING (2018) 146 159
5 DAVIS F.D. PERCEIVED USEFULNESS PERCEIVED EASE OF USE AND USER ACCEPTANCE OF INFORMATION TECHNOLOGY (1989) 129 161
5 SYAM N. SHARMA A. WAITING FOR A SALES RENAISSANCE IN THE FOURTH INDUSTRIAL REVOLUTION: MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE IN SALES RESEAR… 128 137
5 LOGG J.M. MINSON J.A. MOORE D.A. ALGORITHM APPRECIATION: PEOPLE PREFER ALGORITHMIC TO HUMAN JUDGMENT (2019) 126 132
5 DAVENPORT T. GUHA A. GREWAL D. BRESSGOTT T. HOW ARTIFICIAL INTELLIGENCE WILL CHANGE THE FUTURE OF MARKETING (2020) 116 119
5 DAWES R.M. THE ROBUST BEAUTY OF IMPROPER LINEAR MODELS IN DECISION MAKING (1979) 110 110
5 DAVENPORT T.H. RONANKI R. ARTIFICIAL INTELLIGENCE FOR THE REAL WORLD (2018) 108 124
Knowledge Base 6: KB 6
6 BERRY S. LEVINSOHN J. PAKES A. AUTOMOBILE PRICES IN MARKET EQUILIBRIUM (1995) 1263 1284
6 NEVO A. MEASURING MARKET POWER IN THE READY-TO-EAT CEREAL INDUSTRY (2001) 745 751
6 BERRY S.T. ESTIMATING DISCRETE-CHOICE MODELS OF PRODUCT DIFFERENTIATION (1994) 332 353
6 BERRY S. ESTIMATING DISCRETE-CHOICE MODELS OF PRODUCT DIFFERENTIATION (1994) 272 272
6 PETRIN A. QUANTIFYING THE BENEFITS OF NEW PRODUCTS: THE CASE OF THE MINIVAN (2002) 206 206
6 NEVO A. MERGERS WITH DIFFERENTIATED PRODUCTS: THE CASE OF THE READY-TO-EAT CEREAL INDUSTRY (2000) 192 192
6 STOCK J.H. YOGO M. TESTING FOR WEAK INSTRUMENTS IN LINEAR IV REGRESSION (2005) 115 137
6 NEVO A. A PRACTITIONER’S GUIDE TO ESTIMATION OF RANDOM-COEFFICIENTS LOGIT MODELS OF DEMAND (2000) 100 100
6 REYNAERT M. VERBOVEN F. IMPROVING THE PERFORMANCE OF RANDOM COEFFICIENTS DEMAND MODELS: THE ROLE OF OPTIMAL INSTRUMENTS (2014) 82 82
6 STAIGER D. STOCK J.H. INSTRUMENTAL VARIABLES REGRESSION WITH WEAK INSTRUMENTS (1997) 81 92
Knowledge Base 7: KB 7
7 BRYNJOLFSSON E. MCAFEE A. (2014) 917 1699
7 FORD M. (2015) 266 442
7 ARNTZ M. GREGORY T. ZIERAHN U. (2016) 181 397
7 FREY C.B. OSBORNE M.A. (2013) 90 146
7 SCHWAB K. (2016) 72 87
7 PORTER M.E. HEPPELMANN J.E. HOW SMART CONNECTED PRODUCTS ARE TRANSFORMING COMPETITION (2014) 51 70
7 MOKYR J. VICKERS C. ZIEBARTH N.L. THE HISTORY OF TECHNOLOGICAL ANXIETY AND THE FUTURE OF ECONOMIC GROWTH: IS THIS TIME DIFFERENT? (2015) 50 146
7 ZUBOFF S. (1988) 43 61
7 NAMBISAN S. WRIGHT M. FELDMAN M. THE DIGITAL TRANSFORMATION OF INNOVATION AND ENTREPRENEURSHIP: PROGRESS CHALLENGES AND KEY THEMES (2019) 41 47
7 MASON P. (2015) 39 39
Knowledge Base 8: KB 8
8 NIEDERLE M. VESTERLUND L. DO WOMEN SHY AWAY FROM COMPETITION? DO MEN COMPETE TOO MUCH? (2007) 705 714
8 CROSON R. GNEEZY U. GENDER DIFFERENCES IN PREFERENCES (2009) 445 454
8 GNEEZY U. NIEDERLE M. RUSTICHINI A. PERFORMANCE IN COMPETITIVE ENVIRONMENTS: GENDER DIFFERENCES (2003) 372 372
8 DOHMEN T. FALK A. HUFFMAN D. SUNDE U. SCHUPP J. WAGNER G.G. INDIVIDUAL RISK ATTITUDES: MEASUREMENT DETERMINANTS AND BEHAVIORAL CONSEQUENCES (2011) 370 370
8 BUSER T. NIEDERLE M. OOSTERBEEK H. GENDER COMPETITIVENESS AND CAREER CHOICES (2014) 299 299
8 HOLT C.A. LAURY S.K. RISK AVERSION AND INCENTIVE EFFECTS (2002) 258 262
8 FISCHBACHER U. Z-TREE: ZURICH TOOLBOX FOR READY-MADE ECONOMIC EXPERIMENTS (2007) 220 230
8 NIEDERLE M. VESTERLUND L. GENDER AND COMPETITION (2011) 175 175
8 SHURCHKOV O. UNDER PRESSURE: GENDER DIFFERENCES IN OUTPUT QUALITY AND QUANTITY UNDER COMPETITION AND TIME CONSTRAINTS (2012) 157 157
8 GNEEZY U. RUSTICHINI A. GENDER AND COMPETITION AT A YOUNG AGE (2004) 133 133

Development of Knowledge Bases

Technical description

In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).

\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]

The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.

Research Areas: Bibliographic coupling analysis

Research Areas main summary

This is arguably the more interesting part. Here, we identify the literature’s current knowledge frontier by carrying out a bibliographic coupling analysis of the publications in our corpus. This measure uses bibliographical information of publications to establish a similarity relationship between them. Again, method details to be found in the tab Technical description. As you will see, we identify the main research area, but also a set of adjacent research areas with some theoretical/methodological/application overlap.

Main Characteristics

To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.

Categorization

I up to now gain only provide the 10 most central articles, which can be used to classify them

com_name AU PY TI dgr_int TC TC_year
Research Area 1: RA 1
RA 1 AUTOR DH;DORN D;HANSON GH 2016 THE CHINA SHOCK: LEARNING FROM LABOR-MARKET ADJUSTMENT TO LARGE CHANGES IN TRADE 1.9797256 294 49.000000
RA 1 DONALDSON D;HORNBECK R 2016 RAILROADS AND AMERICAN ECONOMIC GROWTH: A “MARKET ACCESS” APPROACH 2.0659329 269 44.833333
RA 1 PIERCE JR;SCHOTT PK 2016 THE SURPRISINGLY SWIFT DECLINE OF US MANUFACTURING EMPLOYMENT 1.5844979 327 54.500000
RA 1 DIAMOND R 2016 THE DETERMINANTS AND WELFARE IMPLICATIONS OF US WORKERS’ DIVERGING LOCATION CHOICES BY SKILL: 1980-2000 2.2411962 231 38.500000
RA 1 HANDLEY K;LIMÃO N 2017 POLICY UNCERTAINTY, TRADE, AND WELFARE: THEORY AND EVIDENCE FOR CHINA AND THE UNITED STATES 2.7080198 178 35.600000
RA 1 BAIER SL;YOTOV YV;ZYLK… 2019 ON THE WIDELY DIFFERING EFFECTS OF FREE TRADE AGREEMENTS: LESSONS FROM TWENTY YEARS OF TRADE INTEGRATION 3.5015430 81 27.000000
RA 1 ACEMOGLU D;AUTOR D;DOR… 2016 IMPORT COMPETITION AND THE GREAT US EMPLOYMENT SAG OF THE 2000S 0.8712633 282 47.000000
RA 1 BLOOM N;DRACA M;VAN RE… 2016 TRADE INDUCED TECHNICAL CHANGE? THE IMPACT OF CHINESE IMPORTS ON INNOVATION, IT AND PRODUCTIVITY 0.6510266 372 62.000000
RA 1 CALIENDO L;DVORKIN M;P… 2019 TRADE AND LABOR MARKET DYNAMICS: GENERAL EQUILIBRIUM ANALYSIS OF THE CHINA TRADE SHOCK 3.2009245 72 24.000000
RA 1 FAJGELBAUM PD;GOLDBERG… 2020 THE RETURN TO PROTECTIONISM 3.2848460 69 34.500000
Research Area 2: RA 2
RA 2 FREY CB;OSBORNE MA 2017 THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION? 2.9795813 1657 331.400000
RA 2 ACEMOGLU D;RESTREPO P 2018 THE RACE BETWEEN MAN AND MACHINE: IMPLICATIONS OF TECHNOLOGY FOR GROWTH, FACTOR SHARES, AND EMPLOYMENT 7.0951618 312 78.000000
RA 2 ACEMOGLU D;RESTREPO P 2020 ROBOTS AND JOBS: EVIDENCE FROM US LABOR MARKETS 6.4471468 230 115.000000
RA 2 BEAUDRY P;GREEN DA;SAN… 2016 THE GREAT REVERSAL IN THE DEMAND FOR SKILL AND COGNITIVE TASKS 8.7871785 118 19.666667
RA 2 DENGLER K;MATTHES B 2018 THE IMPACTS OF DIGITAL TRANSFORMATION ON THE LABOUR MARKET: SUBSTITUTION POTENTIALS OF OCCUPATIONS IN GERMANY 13.2086495 75 18.750000
RA 2 CORTES GM 2016 WHERE HAVE THE MIDDLE-WAGE WORKERS GONE? A STUDY OF POLARIZATION USING PANEL DATA 9.3025208 78 13.000000
RA 2 BÁRÁNY ZL;SIEGEL C 2018 JOB POLARIZATION AND STRUCTURAL CHANGE 11.4954610 47 11.750000
RA 2 DEMING D;KAHN LB 2018 SKILL REQUIREMENTS ACROSS FIRMS AND LABOR MARKETS: EVIDENCE FROM JOB POSTINGS FOR PROFESSIONALS 8.8047922 60 15.000000
RA 2 HERSHBEIN B;KAHN LB 2018 DO RECESSIONS ACCELERATE ROUTINE-BIASED TECHNOLOGICAL CHANGE? EVIDENCE FROM VACANCY POSTINGS 6.5650568 80 20.000000
RA 2 CORTES GM;JAIMOVICH N;… 2017 DISAPPEARING ROUTINE JOBS: WHO, HOW, AND WHY? 11.4540851 43 8.600000
Research Area 3: RA 3
RA 3 HIRSCHI A 2018 THE FOURTH INDUSTRIAL REVOLUTION: ISSUES AND IMPLICATIONS FOR CAREER RESEARCH AND PRACTICE 2.7466983 120 30.000000
RA 3 ARNTZ M;GREGORY T;ZIER… 2017 REVISITING THE RISK OF AUTOMATION 2.0833542 122 24.400000
RA 3 WIRTZ J;PATTERSON PG;K… 2018 BRAVE NEW WORLD: SERVICE ROBOTS IN THE FRONTLINE 0.4762368 467 116.750000
RA 3 RICHINS G;STAPLETON A;… 2017 BIG DATA ANALYTICS: OPPORTUNITY OR THREAT FOR THE ACCOUNTING PROFESSION? 2.1988222 78 15.600000
RA 3 GRAETZ G;MICHAELS G 2018 ROBOTS AT WORK 0.6628245 244 61.000000
RA 3 CALVINO F;VIRGILLITO ME 2018 THE INNOVATION-EMPLOYMENT NEXUS: A CRITICAL SURVEY OF THEORY AND EMPIRICS 2.1978458 71 17.750000
RA 3 SPENCER DA 2018 FEAR AND HOPE IN AN AGE OF MASS AUTOMATION: DEBATING THE FUTURE OF WORK 1.8262616 75 18.750000
RA 3 PIVA M;VIVARELLI M 2018 TECHNOLOGICAL CHANGE AND EMPLOYMENT: IS EUROPE READY FOR THE CHALLENGE? 2.6983642 42 10.500000
RA 3 LEUNG E;PAOLACCI G;PUN… 2018 MAN VERSUS MACHINE: RESISTING AUTOMATION IN IDENTITY-BASED CONSUMER BEHAVIOR 1.7474918 64 16.000000
RA 3 SHESTAKOFSKY B 2017 WORKING ALGORITHMS: SOFTWARE AUTOMATION AND THE FUTURE OF WORK 2.5851687 43 8.600000
Research Area 4: RA 4
RA 4 ADNER R;KAPOOR R 2016 INNOVATION ECOSYSTEMS AND THE PACE OF SUBSTITUTION: RE-EXAMINING TECHNOLOGY S-CURVES 2.1390348 210 35.000000
RA 4 BOGERS M;HADAR R;BILBE… 2016 ADDITIVE MANUFACTURING FOR CONSUMER-CENTRIC BUSINESS MODELS: IMPLICATIONS FOR SUPPLY CHAINS IN CONSUMER GOODS MANUFACTURING 1.3678306 221 36.833333
RA 4 DIETVORST BJ;SIMMONS J… 2018 OVERCOMING ALGORITHM AVERSION: PEOPLE WILL USE IMPERFECT ALGORITHMS IF THEY CAN (EVEN SLIGHTLY) MODIFY THEM 1.1916036 173 43.250000
RA 4 HENGSTLER M;ENKEL E;DU… 2016 APPLIED ARTIFICIAL INTELLIGENCE AND TRUST-THE CASE OF AUTONOMOUS VEHICLES AND MEDICAL ASSISTANCE DEVICES 0.7880578 237 39.500000
RA 4 ROY R;SARKAR M 2016 KNOWLEDGE, FIRM BOUNDARIES, AND INNOVATION: MITIGATING THE INCUMBENT’S CURSE DURING RADICAL TECHNOLOGICAL CHANGE 2.3822935 64 10.666667
RA 4 LEE K;MALERBA F 2017 CATCH-UP CYCLES AND CHANGES IN INDUSTRIAL LEADERSHIP:WINDOWS OF OPPORTUNITY AND RESPONSES OF FIRMS AND COUNTRIES IN THE EV… 0.7098680 210 42.000000
RA 4 LONGONI C;BONEZZI A;MO… 2019 RESISTANCE TO MEDICAL ARTIFICIAL INTELLIGENCE 0.6676156 213 71.000000
RA 4 VERHOEVEN D;BAKKER J;V… 2016 MEASURING TECHNOLOGICAL NOVELTY WITH PATENT-BASED INDICATORS 0.9952424 134 22.333333
RA 4 CHRISTENSEN CM;MCDONAL… 2018 DISRUPTIVE INNOVATION: AN INTELLECTUAL HISTORY AND DIRECTIONS FOR FUTURE RESEARCH 0.7615000 167 41.750000
RA 4 KAPOOR R;AGARWAL S 2017 SUSTAINING SUPERIOR PERFORMANCE IN BUSINESS ECOSYSTEMS: EVIDENCE FROM APPLICATION SOFTWARE DEVELOPERS IN THE IOS AND ANDRO… 0.9758794 129 25.800000
Research Area 5: RA 5
RA 5 KEES J;BERRY C;BURTON … 2017 AN ANALYSIS OF DATA QUALITY: PROFESSIONAL PANELS, STUDENT SUBJECT POOLS, AND AMAZON’S MECHANICAL TURK 3.4581968 450 90.000000
RA 5 PALAN S;SCHITTER C 2018 PROLIFIC.AC—A SUBJECT POOL FOR ONLINE EXPERIMENTS 1.6715188 673 168.250000
RA 5 GOODMAN JK;PAOLACCI G 2017 CROWDSOURCING CONSUMER RESEARCH 3.5388239 252 50.400000
RA 5 CHEUNG JH;BURNS DK;SIN… 2017 AMAZON MECHANICAL TURK IN ORGANIZATIONAL PSYCHOLOGY: AN EVALUATION AND PRACTICAL RECOMMENDATIONS 3.3234447 236 47.200000
RA 5 ARECHAR AA;GÄCHTER S;M… 2018 CONDUCTING INTERACTIVE EXPERIMENTS ONLINE 5.0011265 100 25.000000
RA 5 WESSLING KS;HUBER J;NE… 2017 MTURK CHARACTER MISREPRESENTATION: ASSESSMENT AND SOLUTIONS 2.7985596 178 35.600000
RA 5 HULLAND J;BAUMGARTNER … 2018 MARKETING SURVEY RESEARCH BEST PRACTICES: EVIDENCE AND RECOMMENDATIONS FROM A REVIEW OF JAMS ARTICLES 1.4405568 288 72.000000
RA 5 PORTER COLH;OUTLAW R;G… 2019 THE USE OF ONLINE PANEL DATA IN MANAGEMENT RESEARCH: A REVIEW AND RECOMMENDATIONS 4.1904259 85 28.333333
RA 5 AGUINIS H;VILLAMOR I;R… 2021 MTURK RESEARCH: REVIEW AND RECOMMENDATIONS 2.2140191 119 119.000000
RA 5 STRITCH JM;PEDERSEN MJ… 2017 THE OPPORTUNITIES AND LIMITATIONS OF USING MECHANICAL TURK (MTURK) IN PUBLIC ADMINISTRATION AND MANAGEMENT SCHOLARSHIP 3.3344001 77 15.400000
Research Area 6: RA 6
RA 6 FISHER M;GALLINO S;LI J 2018 COMPETITION-BASED DYNAMIC PRICING IN ONLINE RETAILING: A METHODOLOGY VALIDATED WITH FIELD EXPERIMENTS 3.0368615 50 12.500000
RA 6 BJÖRNERSTEDT J;VERBOVEN F 2016 DOES MERGER SIMULATION WORK? EVIDENCE FROM THE SWEDISH ANALGESICS MARKET 3.5082049 37 6.166667
RA 6 DELLAVIGNA S;GENTZKOW M 2019 UNIFORM PRICING IN U.S. RETAIL CHAINS 2.0555565 59 19.666667
RA 6 CRAWFORD GS;PAVANINI N… 2018 ASYMMETRIC INFORMATION AND IMPERFECT COMPETITION IN LENDING MARKETS 3.7332749 30 7.500000
RA 6 LI Z;AGARWAL A 2017 PLATFORM INTEGRATION AND DEMAND SPILLOVERS IN COMPLEMENTARY MARKETS: EVIDENCE FROM FACEBOOK’S INTEGRATION OF INSTAGRAM 1.9988122 55 11.000000
RA 6 DUCH-BROWN N;GRZYBOWSK… 2017 THE IMPACT OF ONLINE SALES ON CONSUMERS AND FIRMS. EVIDENCE FROM CONSUMER ELECTRONICS 3.0262415 36 7.200000
RA 6 BAYER P;MCMILLAN R;MUR… 2016 A DYNAMIC MODEL OF DEMAND FOR HOUSES AND NEIGHBORHOODS 1.5436674 59 9.833333
RA 6 ROMERO JP;MCCOMBIE JSL 2016 THE MULTI-SECTORAL THIRLWALL’S LAW: EVIDENCE FROM 14 DEVELOPED EUROPEAN COUNTRIES USING PRODUCT-LEVEL DATA 2.2973800 38 6.333333
RA 6 GUAJARDO JA;COHEN MA;N… 2016 SERVICE COMPETITION AND PRODUCT QUALITY IN THE U.S. AUTOMOBILE INDUSTRY 1.6070041 50 8.333333
RA 6 EGAN M;HORTAÇSU A;MATV… 2017 DEPOSIT COMPETITION AND FINANCIAL FRAGILITY: EVIDENCE FROM THE US BANKING SECTOR 1.3888507 53 10.600000
Research Area 7: RA 7
RA 7 CROSETTO P;FILIPPIN A 2016 A THEORETICAL AND EXPERIMENTAL APPRAISAL OF FOUR RISK ELICITATION METHODS 1.7172639 76 12.666667
RA 7 GILLEN B;SNOWBERG E;YA… 2019 EXPERIMENTING WITH MEASUREMENT ERROR: TECHNIQUES WITH APPLICATIONS TO THE CALTECH COHORT STUDY 2.7660502 47 15.666667
RA 7 SACCARDO S;PIETRASZ A;… 2018 ON THE SIZE OF THE GENDER DIFFERENCE IN COMPETITIVENESS 4.9619422 26 6.500000
RA 7 BERTRAND M 2018 COASE LECTURE – THE GLASS CEILING 3.3515240 33 8.250000
RA 7 DE PAOLA M;GIOIA F 2016 WHO PERFORMS BETTER UNDER TIME PRESSURE? RESULTS FROM A FIELD EXPERIMENT 3.2514685 32 5.333333
RA 7 BURSZTYN L;FUJIWARA T;… 2017 ‘ACTING WIFE’: MARRIAGE MARKET INCENTIVES AND LABOR MARKET INVESTMENTS 1.2942531 70 14.000000
RA 7 BUSER T 2016 THE IMPACT OF LOSING IN A COMPETITION ON THE WILLINGNESS TO SEEK FURTHER CHALLENGES 2.6978214 31 5.166667
RA 7 IRIBERRI N;REY-BIEL P 2017 STEREOTYPES ARE ONLY A THREAT WHEN BELIEFS ARE REINFORCED: ON THE SENSITIVITY OF GENDER DIFFERENCES IN PERFORMANCE UNDER C… 4.0635184 20 4.000000
RA 7 LIST JA;SHAIKH AM;XU Y 2019 MULTIPLE HYPOTHESIS TESTING IN EXPERIMENTAL ECONOMICS 0.9863359 82 27.333333
RA 7 BERLIN N;DARGNIES M-P 2016 GENDER DIFFERENCES IN REACTIONS TO FEEDBACK AND WILLINGNESS TO COMPETE 3.7264923 19 3.166667
Research Area 8: RA 8
NA LI S;TONG L;XING J;ZHOU Y 2017 THE MARKET FOR ELECTRIC VEHICLES: INDIRECT NETWORK EFFECTS AND POLICY DESIGN 2.4202453 84 16.800000
NA CENNAMO C;SANTALÓ J 2019 GENERATIVITY TENSION AND VALUE CREATION IN PLATFORM ECOSYSTEMS 1.8467858 58 19.333333
NA COYLE D 2017 PRECARIOUS AND PRODUCTIVE WORK IN THE DIGITAL ECONOMY 2.0304216 31 6.200000
NA KOULAYEV S;RYSMAN M;SC… 2016 EXPLAINING ADOPTION AND USE OF PAYMENT INSTRUMENTS BY US CONSUMERS 0.4083818 44 7.333333
NA TAN G;ZHOU J 2021 THE EFFECTS OF COMPETITION AND ENTRY IN MULTI-SIDED MARKETS 2.2473465 7 7.000000
NA BOKRANTZ J;SKOOGH A;BE… 2020 SMART MAINTENANCE: A RESEARCH AGENDA FOR INDUSTRIAL MAINTENANCE MANAGEMENT 0.3216483 41 20.500000
NA KABRA A;BELAVINA E;GIR… 2020 BIKE-SHARE SYSTEMS: ACCESSIBILITY AND AVAILABILITY 0.2651949 37 18.500000
NA BANDIERA O;PRAT A;HANS… 2020 CEO BEHAVIOR AND FIRM PERFORMANCE 0.2313594 35 17.500000
NA WATANABE C;NAVEED K;NE… 2017 CONSOLIDATED CHALLENGE TO SOCIAL DEMAND FOR RESILIENT PLATFORMS - LESSONS FROM UBER’S GLOBAL EXPANSION 0.1954407 40 8.000000
NA IVALDI M;MULLER-VIBES C 2018 THE DIFFERENTIATED EFFECT OF ADVERTISING ON READERSHIP: EVIDENCE FROM A TWO-SIDED MARKET APPROACH 2.3932281 3 0.750000

Development

Connectivity between the research areas

Knowledge Bases, Research Areas & Topics

Technical description

In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.

\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]

Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).

\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]

More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.

Endnotes

All results are preliminary so far…